{"id":"https://openalex.org/W4387250073","doi":"https://doi.org/10.1109/tgrs.2023.3317079","title":"Adversarial Domain Alignment With Contrastive Learning for Hyperspectral Image Classification","display_name":"Adversarial Domain Alignment With Contrastive Learning for Hyperspectral Image Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387250073","doi":"https://doi.org/10.1109/tgrs.2023.3317079"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3317079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3317079","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100453033","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0001-9752-9530"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]},{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9752-9530","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047590401","display_name":"Wenfei Gao","orcid":"https://orcid.org/0009-0003-0101-4228"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenfei Gao","raw_affiliation_strings":["School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0003-0101-4228","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100625089","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0002-5999-2361"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Liu","raw_affiliation_strings":["School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5999-2361","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059262797","display_name":"Xu Tang","orcid":"https://orcid.org/0000-0003-1375-0778"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Tang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-1375-0778","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020302879","display_name":"Liang Xiao","orcid":"https://orcid.org/0000-0003-0178-9384"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Xiao","raw_affiliation_strings":["School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-0178-9384","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering and the Jiangsu Key Laboratory of Spectral Imaging and Intelligent Sense, Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":1.5557,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83953214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"20"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9746000170707703,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9440000057220459,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7983978986740112},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7359961271286011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6165122389793396},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5226278305053711},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5218340754508972},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.48676514625549316},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4388976991176605},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4360502064228058},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41983795166015625},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4164436459541321},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2769121825695038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7983978986740112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7359961271286011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6165122389793396},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5226278305053711},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5218340754508972},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.48676514625549316},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4388976991176605},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4360502064228058},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41983795166015625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4164436459541321},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2769121825695038},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3317079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3317079","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G2655180113","display_name":null,"funder_award_id":"JSGP202101","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G292805373","display_name":null,"funder_award_id":"62001226","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5324547038","display_name":null,"funder_award_id":"62171332","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5495545777","display_name":null,"funder_award_id":"62071233","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6190154228","display_name":null,"funder_award_id":"61802190","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6397150987","display_name":null,"funder_award_id":"22R04","funder_id":"https://openalex.org/F4320326938","funder_display_name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing"},{"id":"https://openalex.org/G6529097563","display_name":null,"funder_award_id":"JSGP202204","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8432856719","display_name":null,"funder_award_id":"61871226","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8460510842","display_name":null,"funder_award_id":"61906093","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326938","display_name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing","ror":"https://ror.org/02bpap860"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1534408902","https://openalex.org/W1977088242","https://openalex.org/W2029316659","https://openalex.org/W2092745549","https://openalex.org/W2136251662","https://openalex.org/W2153353890","https://openalex.org/W2154240401","https://openalex.org/W2176950688","https://openalex.org/W2314785379","https://openalex.org/W2462239623","https://openalex.org/W2572303978","https://openalex.org/W2611655888","https://openalex.org/W2732412926","https://openalex.org/W2762468750","https://openalex.org/W2766208323","https://openalex.org/W2767074788","https://openalex.org/W2767805377","https://openalex.org/W2771181228","https://openalex.org/W2791006446","https://openalex.org/W2798991696","https://openalex.org/W2894165434","https://openalex.org/W2898204262","https://openalex.org/W2902323880","https://openalex.org/W2914331134","https://openalex.org/W2940678725","https://openalex.org/W2980023149","https://openalex.org/W3001411605","https://openalex.org/W3005680577","https://openalex.org/W3006984222","https://openalex.org/W3012405452","https://openalex.org/W3017352050","https://openalex.org/W3034953390","https://openalex.org/W3035524453","https://openalex.org/W3036224891","https://openalex.org/W3047443805","https://openalex.org/W3048631361","https://openalex.org/W3096655658","https://openalex.org/W3099850646","https://openalex.org/W3102692100","https://openalex.org/W3103695279","https://openalex.org/W3132867842","https://openalex.org/W3158900180","https://openalex.org/W3197866960","https://openalex.org/W3200544749","https://openalex.org/W3209540366","https://openalex.org/W3215515486","https://openalex.org/W3216860461","https://openalex.org/W4205276321","https://openalex.org/W4207045938","https://openalex.org/W4210927230","https://openalex.org/W4224938958","https://openalex.org/W4226182700","https://openalex.org/W4226275810","https://openalex.org/W4283760989","https://openalex.org/W4285114990","https://openalex.org/W4293193074","https://openalex.org/W4296913316","https://openalex.org/W4312269131","https://openalex.org/W4312498943","https://openalex.org/W4312772581","https://openalex.org/W4313476641","https://openalex.org/W4313555298","https://openalex.org/W4318586076","https://openalex.org/W4323914429","https://openalex.org/W4327522253","https://openalex.org/W4378194596","https://openalex.org/W4385864282","https://openalex.org/W6772329248","https://openalex.org/W6774314701","https://openalex.org/W6776535907","https://openalex.org/W6779997284"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W3034375524","https://openalex.org/W2027399350","https://openalex.org/W2060875994","https://openalex.org/W2044184146","https://openalex.org/W2019190440","https://openalex.org/W3034864990"],"abstract_inverted_index":{"Recently,":[0],"deep":[1],"learning-based":[2],"hyperspectral":[3],"image":[4],"(HSI)":[5],"classification":[6,63,169],"techniques":[7],"are":[8,80,148],"flourishing":[9],"and":[10,35,77,84,93,101,139,174,186],"exhibit":[11],"good":[12],"performance,":[13],"where":[14,141],"cross":[15],"domain":[16,34,37,52],"information":[17],"is":[18,58,120,133,159,178],"usually":[19],"utilized":[20],"to":[21,41,65,106,125,135,150],"reduce":[22],"the":[23,30,61,94,145,167,171,175,190,195,199],"dependency":[24],"on":[25,98,182],"large":[26],"labeled":[27],"samples.":[28],"However,":[29],"gap":[31],"between":[32],"source":[33,100,184],"target":[36,102,188],"makes":[38],"it":[39],"difficult":[40],"carry":[42],"out":[43],"knowledge":[44],"transfer":[45],"directly.":[46],"In":[47,73,104],"this":[48],"paper,":[49],"an":[50,89],"adversarial":[51,90,95,172],"alignment":[53,76,79,124],"with":[54,112,153],"contrastive":[55,131,176],"learning":[56,91,132,164],"method":[57,197],"designed":[59],"for":[60,110],"HSI":[62],"task":[64],"achieve":[66],"feature":[67],"consistency":[68],"that":[69,194],"benefits":[70],"transferring":[71],"knowledge.":[72],"details,":[74],"spectral":[75],"semantic":[78,123],"conducted":[81,160],"in":[82,88,122,161],"local":[83],"global":[85],"levels":[86],"respectively":[87],"way,":[92],"loss":[96,173,177],"acts":[97],"both":[99,137],"domains.":[103],"order":[105],"learn":[107],"specific":[108],"features":[109,128],"objects":[111],"different":[113],"spatial":[114],"scales,":[115],"a":[116,162],"multi-scale":[117],"selection":[118],"module":[119],"constructed":[121],"select":[126],"channel":[127],"adaptively.":[129],"Moreover,":[130],"employed":[134],"increase":[136],"robustness":[138],"sensitiveness,":[140],"augmented":[142],"data":[143],"from":[144],"same/different":[146],"samples":[147],"forced":[149],"be":[151],"similar/dissimilar":[152],"each":[154],"other.":[155],"The":[156],"training":[157],"process":[158],"few-shot":[163,168],"way":[165],"then":[166],"loss,":[170],"optimized":[179],"together.":[180],"Tested":[181],"one":[183],"dataset":[185],"four":[187],"datasets,":[189],"experimental":[191],"results":[192],"show":[193],"proposed":[196],"outperforms":[198],"other":[200],"comparisons.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}